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How to Accelerate Your Real-Time Fraud Detection

According to a recent survey from PYMNTS, over 71% of executives are significantly interested in real-time payment systems. It’s easy to see the value in near-instant transactions – faster account openings, purchase confirmations, fund transfers between banks, amongst others. These benefit businesses, consumer and financial institutions (FIs) Even the Federal Reserve is interested in real-time payments and is planning to launch its FedNow platform in mid-2023. 

Of course, the financial crime industry sees the potential in real-time payments too, being able to move money through fake accounts, increasing the chance of cashing out transfers or receiving goods fraudulently purchased.course, the financial crime industry sees the potential in real-time payments, too. Already, we are seeing an uptick in fraudulent behavior stemming from the ease of instant, bank-to-bank transfer apps. In 2021, 80% of financial institutions noticed a spike in fraud losses after incorporating real-time payments into their strategy. 

However, faster processinig and payment methods don’t have to be synonymous with risks for financial institutions or consumers. While fraudsters are accelerating and expanding their operations, FIs can leverage powerful fraud detection systems to counter fraud losses and identify a fraudulent transaction or account earlier.

But before we get into the details of the solution, let’s review modern fraudulent behavior.  

Fraudsters are getting faster

Real-time data and sophisticated financial crime strategies have allowed cybercriminals to accelerate their operations. Today, it’s possible for fraudsters to develop synthetic IDs and steal user credentials in a blink of an eye. In some cases, as with payment authorization fraud, scammers can manipulate businesses and individuals into paying them hundreds of dollars instantly—with little protection for banks or their customers. 

It can take months, sometimes over a year, to identify fraud. Both external and internal fraud attempts can be difficult to diagnose, yet with uncertain times and the frequency of online shopping and Card Not Present (CNP) transactions, this trend is bound to worsen.

For banking fraud departments, the rapidly accelerating rate of fraud across the board means it’s time to review strategy and tools. And the best solutions use real-time data. 

Fraud detection in banking 

As fraud accelerates, caseloads increase at financial institutions. Smaller and mid-sized banks, credit unions and lenders often must rely on outdated and sluggish systems, as well as fragile and lengthy manual analysis processes, creating numerous vulnerabilities. And fraudsters know it.

The problem many financial institutions are facing is that they are attempting to fight modern fraud with decades-old technology. These tools require significant manual input, lack transparency, and take hours, if not days, to review. As a result, case management across financial products and departments, even if you exclude customer service monitoring, takes significant team bandwidth. But the results are largely ineffective. 

For real time fraud detection, banks require a platform that takes several factors into account:

  • Omnichannel support
  • Near-instant data-syncing
  • Automated workflows
  • Account opening, transaction, and KYC/AML support
  • No code, easy to use
  • Easily integrated into current anti-fraud processes
  • Machine learning for continuous optimization and adaptation to new fraud patterns
  • A fast, customer-centric workflow to avoid abandonment rates

Until recently, real-time fraud detection was difficult to maintain and largely unaffordable for anything other than a large, enterprise-level bank. But through data partnerships, this technology has become accessible to smaller financial institutions, through tools that aggregate this data and transforms them into business decisions.

How to accelerate fraud risk analysis

When it comes to fraud prevention, speed is everything. Having enough time to remedy the problem before it gets out of hand saves money, time, and a long-term brand reputation. Accurate analysis can also prevent the likelihood of false positives, further ensuring a stellar customer experience. 

But to get to that point, it’s important to follow these three steps to accelerate your fraud risk analysis process effectively. 

Discover your bottlenecks

Bottlenecks in the anti-fraud process are common, and in processes as time-consuming as risk analysis, these lags build up quickly. There are many reasons these holds can occur, from inefficient technology to an overreliance on IT, to working with siloed data. 

After mapping out the entire fraud process for your organization, it’s time to highlight where people get stuck the most. Then you can identify what would likely speed up the process. In many cases, such as case management, automation can significantly reduce the workload. In other areas, ensuring that data is synced in real-time can prevent lags in identifying suspicious activity. 

Understand the technology

Next, you’ll want to clarify what technology would make sense for each step you want to accelerate. Not all platforms are equal, and you will likely need insight from your CTO and IT team. 

For example, automation has several variations. Is it a simple yet efficient non-intelligent variation known as Robotic Process Automation (RPA)? Or does a proposed solution include artificial intelligence (AI), particularly machine learning (ML), for optimization and scale? Both options may improve on a highly-manual method, but organizations that leverage AI and ML can scale as they grow with the same system. 

This also applies to how a third-party software or data partner handles its security protocol. How does it maintain compliance, and how secure is sensitive information if it passes through the software? 

Keep the process simple 

Finally, once you identify places for improvement, you’ll want to keep the process as simple as possible for employees. There are many ways to keep fraud management painless, from using no-code solutions to integrating your solution with legacy software. 

How you use your new technology will largely depend on your current system and the new solution and how they interact. Ideally, your new technology will also offer training sessions for your employees to make the transition as seamless as possible. 

But, software aside, the easier and less complex you can keep your risk analysis process – while intelligently applying new strategies and insights, as well as facilitating collaboration and knowledge sharing – the easier it will be to maintain in the long term without compromising the effectiveness and robustness of your fraud identification process.

Real-time fraud detection made easy

Decades ago, real-time data and a comprehensive fraud detection system were largely out of reach for smaller and mid-sized FIs. But with the democratization of data and enhanced technology, real-time fraud risk analysis and solutions are now available. You no longer need to build this in-house or use rigid plugins. Partnerships with your chosen fraud management system provide FIs with an opportunity not only to leverage essential tech but also to compete with enterprise-level banks — without the extensive capital required for legacy solutions. 

 

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Stan Cowan

Stan Cowan

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04 Oct 2022

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This post is from a series of posts in the group:

Payments strategies 2015-2020-2030

Payments systems visions, strategies, trends, pilots, forecasting, and planning for the short-, medium-, and far-term.


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